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- Creators: Barrett, The Honors College
- Creators: Lee, Hyunglae
- Member of: Theses and Dissertations
Description
The 21st century engineer will face a diverse set of challenges spread out along a broad spectrum of disciplines. Among others, the fields of energy, healthcare, cyberspace, virtual reality, and neuroscience require monumental efforts by the new generation of engineers to meet the demands of a growing society. However the most important, and likely the most under recognized, challenge lies in developing advanced personalized learning. It is the core foundation from which the rest of the challenges can be accomplished. Without an effective method of teaching engineering students how to realize these grand challenges, the knowledge pool from which to draw new innovations and discoveries will be greatly diminished. This paper introduces the Inventors Workshop (IW), a hands-on, passion-based approach to personalized learning. It is intended to serve as a manual that will inform the next generation of student leaders and inventioneers about the core concepts the Inventors Workshop was built upon, and how to continue improvement into the future. Due to the inherent complexities in the grand challenge of personalized learning, the IW has developed a multifaceted solution that is difficult to explain in a single phrase. To enable comprehension of the IW's full vision, the process undergone to date of establishing and expanding the IW is described. In addition, research has been conducted to determine a variety of paths the Inventors Workshop may utilize in future expansion. Each of these options is explored and related to the core foundations of the IW to assist future leaders and partners in effectively improving personalized learning at ASU and beyond.
ContributorsEngelhoven, V. Logan (Author) / Burleson, Winslow (Thesis director) / Peck, Sidnee (Committee member) / Fortun, A. L. Cecil (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12
Description
The data and results presented in this paper are part of a continuing effort to innovate and pioneer the future of engineering. The purpose of the following is to demonstrate the mechanical buckling characteristics in stiff thin film and soft substrate systems, and the importance of controlling them. In today's engineering research, wrinkling in systems in beginning to be viewed as a means for engineering innovation rather than failure. This research is important to further progress the possible applications the technology proposes, such as flexible electronics and tunable adhesives. This work utilizes a cost efficient and relatively easy method for generating and analyzing buckled systems. Ultra violate oxidation at ambient temperatures is exploited to create a stiff thin surface on rubber like polydimethylsiloxane, and couple with strain induction wrinkles are generated. Wrinkle characteristics such as amplitude, wavelengths and wetting properties were investigated. In simple cases, trends were confirmed that increased oxidation relates to increased buckle wavelengths, and increase in strain corresponds to a decrease in wavelength. Hierarchical buckles were produced in one-dimensional systems treated with a multi-step method; these were the first to be generated in the ASU labs. Unique topographic changes were produced in two-dimensional systems treated with the same method. Honeycomb or dome like structures were noted to occur, important as they undergo a different energy-reliving configuration compared to traditional parallel buckles. The information provided characterizes many aspects of the buckle phenomena and will allow for further inquiry into specific functions utilizing the technology to continue advancements in engineering.
ContributorsValacich, Michael James (Author) / Jiang, Hanqing (Thesis director) / Yu, Hongyu (Committee member) / Teng, Ma (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2013-05
Description
The goal of this research is to compare the mechanical properties of CP-Ti and Ti-O and to understand the relationship between a material's microstructure and its response to fatigue. Titanium has been selected due to its desirable properties and applicability in several engineering fields. Both samples are polished and etched in order to visualize and characterize the microstructure and its features. The samples then undergo strain-controlled fatigue tests for several thousand cycles. Throughout testing, images of the samples are taken at zero and maximum load for DIC analysis. The DIC results can be used to study the local strains of the samples. The DIC analysis performed on the CP-Ti sample and presented in this study will be used to understand how the addition of oxygen in the Ti-O impacts fatigue response. The outcome of this research can be used to develop long-lasting, high strength materials.
ContributorsRiley, Erin Ashland (Author) / Solanki, Kiran (Thesis director) / Oswald, Jay (Committee member) / School of Art (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant directions. Twenty healthy young adults were recruited to perform quiet standing tasks on the platform. Conventional stability measures, namely center-of-pressure (COP) path length and COP area, were also adopted for further comparisons with the proposed VTC. The results indicated that postural balance was adversely impacted, evidenced by significant decreases in VTC and increases in COP path length/area measures, as the ground compliance increased and/or in the absence of vision (ps < 0.001). Interaction effects between environment and vision were observed in VTC and COP path length measures (ps ≤ 0.05), but not COP area (p = 0.103). The estimated likelihood of falls in anterior-posterior (AP) and medio-lateral (ML) directions converged to nearly 50% (almost independent of the foot setting) as the experimental condition became significantly challenging.
The second study introduces a deep learning approach using convolutional neural network (CNN) for predicting environments based on instant observations of sway during balance tasks. COP data were collected from fourteen subjects while standing on the 2D compliant environments. Different window sizes for data segmentation were examined to identify its minimal length for reliable prediction. Commonly-used machine learning models were also tested to compare their effectiveness with that of the presented CNN model. The CNN achieved above 94.5% in the overall prediction accuracy even with 2.5-second length data, which cannot be achieved by traditional machine learning models (ps < 0.05). Increasing data length beyond 2.5 seconds slightly improved the accuracy of CNN but substantially increased training time (60% longer). Importantly, averaged normalized confusion matrices revealed that CNN is much more capable of differentiating the mid-level environmental condition.
These two studies provide new perspectives in human postural balance, which cannot be
interpreted by conventional stability analyses. Outcomes of these studies contribute to the advancement of human interactive robots/devices for fall prevention and rehabilitation.
ContributorsPhan, Vu Nguyen (Author) / Lee, Hyunglae (Thesis advisor) / Peterson, Daniel (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2021
Description
Technological progress in robot sensing, design, and fabrication, and the availability of open source software frameworks such as the Robot Operating System (ROS), are advancing the applications of swarm robotics from toy problems to real-world tasks such as surveillance, precision agriculture, search-and-rescue, and infrastructure inspection. These applications will require the development of robot controllers and system architectures that scale well with the number of robots and that are robust to robot errors and failures. To achieve this, one approach is to design decentralized robot control policies that require only local sensing and local, ad-hoc communication. In particular, stochastic control policies can be designed that are agnostic to individual robot identities and do not require a priori information about the environment or sophisticated computation, sensing, navigation, or communication capabilities. This dissertation presents novel swarm control strategies with these properties for detecting and mapping static targets, which represent features of interest, in an
unknown, bounded, obstacle-free environment. The robots move on a finite spatial grid according to
the time-homogeneous transition probabilities of a Discrete-Time Discrete-State (DTDS) Markov chain model, and they exchange information with other robots within their communication range using a consensus (agreement) protocol. This dissertation extend theoretical guarantees on multi-robot consensus over fixed and time-varying communication networks with known connectivity properties to consensus over the networks that have Markovian switching dynamics and no presumed connectivity. This dissertation develops such swarm consensus strategies for detecting a single feature in the environment, tracking multiple features, and reconstructing a discrete distribution of features modeled as an occupancy grid map.
The proposed consensus approaches are validated in numerical simulations and in 3D physics-based simulations of quadrotors in Gazebo. The scalability of the proposed approaches is examined through extensive numerical simulation studies over different swarm populations and environment sizes.
ContributorsShirsat, Aniket (Author) / Berman, Spring (Thesis advisor) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Saripalli, Srikanth (Committee member) / Gharavi, Lance (Committee member) / Arizona State University (Publisher)
Created2022
Description
This study experimentally investigated a selected methodology of mechanical torque testing of 3D printed gears. The motivation for pursuing this topic of research stemmed from a previous experience of one of the team members that propelled inspiration to quantify how different variables associated with 3D printing affect the structural integrity of the resulting piece. With this goal in mind, the team set forward with creating an experimental set-up and the construction of a test rig. However, due to restrictions in time and other unforeseen circumstances, this thesis underwent a change in scope. The new scope focused solely on determining if the selected methodology of mechanical torque testing was valid. Following the securement of parts and construction of a test rig, the team was able to conduct mechanical testing. This testing was done multiple times on an identically printed gear. The data collected showed results similar to a stress-strain curve when the torque was plotted against the angle of twist. In the resulting graph, the point of plastic deformation is clearly visible and the maximum torque the gear could withstand is clearly identifiable. Additionally, across the tests conducted, the results show high similarity in results. From this, it is possible to conclude that if the tests were repeated multiple times the maximum possible torque could be found. From that maximum possible torque, the mechanical strength of the tested gear could be identified.
ContributorsGarcia, Andres (Author) / Parekh, Mohan (Co-author) / Middleton, James (Thesis director) / Murthy, Raghavendra (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2023-05
Description
This study experimentally investigated a selected methodology of mechanical torque testing of 3D printed gears. The motivation for pursuing this topic of research stemmed from a previous experience of one of the team members that propelled inspiration to quantify how different variables associated with 3D printing affect the structural integrity of the resulting piece. With this goal in mind, the team set forward with creating an experimental set-up and the construction of a test rig. However, due to restrictions in time and other unforeseen circumstances, this thesis underwent a change in scope. The new scope focused solely on determining if the selected methodology of mechanical torque testing was valid. Following the securement of parts and construction of a test rig, the team was able to conduct mechanical testing. This testing was done multiple times on an identically printed gear. The data collected showed results similar to a stress-strain curve when the torque was plotted against the angle of twist. In the resulting graph, the point of plastic deformation is clearly visible and the maximum torque the gear could withstand is clearly identifiable. Additionally, across the tests conducted, the results show high similarity in results. From this, it is possible to conclude that if the tests were repeated multiple times the maximum possible torque could be found. From that maximum possible torque, the mechanical strength of the tested gear could be identified.
ContributorsParekh, Mohan (Author) / Garcia, Andres (Co-author) / Middleton, James (Thesis director) / Murthy, Raghavendra (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2023-05
Description
This dissertation introduces and examines Soft Curved Reconfigurable Anisotropic Mechanisms (SCRAMs) as a solution to address actuation, manufacturing, and modeling challenges in the field of soft robotics, with the aim of facilitating the broader implementation of soft robots in various industries. SCRAM systems utilize the curved geometry of thin elastic structures to tackle these challenges in soft robots. SCRAM devices can modify their dynamic behavior by incorporating reconfigurable anisotropic stiffness, thereby enabling tailored locomotion patterns for specific tasks. This approach simplifies the actuation of robots, resulting in lighter, more flexible, cost-effective, and safer soft robotic systems. This dissertation demonstrates the potential of SCRAM devices through several case studies. These studies investigate virtual joints and shape change propagation in tubes, as well as anisotropic dynamic behavior in vibrational soft twisted beams, effectively demonstrating interesting locomotion patterns that are achievable using simple actuation mechanisms. The dissertation also addresses modeling and simulation challenges by introducing a reduced-order modeling approach. This approach enables fast and accurate simulations of soft robots and is compatible with existing rigid body simulators. Additionally, this dissertation investigates the prototyping processes of SCRAM devices and offers a comprehensive framework for the development of these devices. Overall, this dissertation demonstrates the potential of SCRAM devices to overcome actuation, modeling, and manufacturing challenges in soft robotics. The innovative concepts and approaches presented have implications for various industries that require cost-effective, adaptable, and safe robotic systems. SCRAM devices pave the way for the widespread application of soft robots in diverse domains.
ContributorsJiang, Yuhao (Author) / Aukes, Daniel (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Srivastava, Siddharth (Committee member) / Arizona State University (Publisher)
Created2023
Description
This thesis presents a study on the user adaptive variable impedance control of a wearable ankle robot for robot-aided rehabilitation with a primary focus on enhancing accuracy and speed. The controller adjusts the impedance parameters based on the user's kinematic data to provide personalized assistance. Bayesian optimization is employed to minimize an objective function formulated from the user's kinematic data to adapt the impedance parameters per user, thereby enhancing speed and accuracy. Gaussian process is used as a surrogate model for optimization to account for uncertainties and outliers inherent to human experiments. Student-t process based outlier detection is utilized to enhance optimization robustness and accuracy. The efficacy of the optimization is evaluated based on measures of speed, accuracy, and effort, and compared with an untuned variable impedance controller during 2D curved trajectory following tasks. User effort was measured based on muscle activation data from the tibialis anterior, peroneus longus, soleus, and gastrocnemius muscles. The optimized controller was evaluated on 15 healthy subjects and demonstrated an average increase in speed of 9.85% and a decrease in deviation from the ideal trajectory of 7.57%, compared to an unoptimized variable impedance controller. The strategy also reduced the time to complete tasks by 6.57%, while maintaining a similar level of user effort.
ContributorsManoharan, Gautham (Author) / Lee, Hyunglae (Thesis advisor) / Berman, Spring (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2023
Description
The Soft Robotic Hip Exosuit (SR-HExo) was designed, fabricated, and tested in treadmill walking experiments with healthy participants to gauge effectivity of the suit in assisting locomotion and in expanding the basin of entrainment as a method of rehabilitation. The SR-HExo consists of modular, compliant materials to move freely with a user’s range of motion and is actuated with X-oriented flat fabric pneumatic artificial muscles (X-ff-PAM) that contract when pressurized and can generate 190N of force at 200kPa in a 0.3 sec window. For use in gait assistance experiments, X-ff-PAM actuators were placed anterior and posterior to the right hip joint. Extension assistance and flexion assistance was provided in 10-45% and 50-90% of the gait cycle, respectively. Device effectivity was determined through range of motion (ROM) preservation and hip flexor and extensor muscular activity reduction. While the active suit reduced average hip ROM by 4o from the target 30o, all monitored muscles experienced significant reductions in electrical activity. The gluteus maximus and biceps femoris experienced electrical activity reduction of 13.1% and 6.6% respectively and the iliacus and rectus femoris experienced 10.7% and 27.7% respectively. To test suit rehabilitative potential, the actuators were programmed to apply periodic torque perturbations to induce locomotor entrainment. An X-ff-PAM was contracted at
the subject’s preferred gait frequency and, in randomly ordered increments of 3%, increased up to 15% beyond.
Perturbations located anterior and posterior to the hip were tested separately to assess impact of location on entrainment characteristics. All 11 healthy participants achieved entrainment in all 12 experimental conditions in both
suit orientations. Phase-locking consistently occurred around toe-off phase of the gait cycle (GC). Extension perturbations synchronized earlier in the gait cycle (before 60% GC where peak hip extension occurs) than flexion perturbations (just after 60% GC at the transition from full hip extension to hip flexion), across group averaged results. The study demonstrated the suit can significantly extend the basin of entrainment and improve transient response compared to previously reported results and confirms that a single stable attractor exists during gait entrainment to unidirectional hip perturbations.
ContributorsBaye-Wallace, Lily (Author) / Lee, Hyunglae (Thesis advisor) / Marvi, Hamidreza (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2021